David John Lary

David John Lary
University of Texas at Dallas | UTD · Physics

BSc (Kings College, First Class Double Honors), PhD (Cambridge)

About

190
Publications
48,705
Reads
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4,039
Citations
Additional affiliations
May 2010 - present
University of Texas at Dallas
Position
  • Professor (Associate)
October 2001 - May 2010
NASA
Position
  • Distinguished Goddard Fellow
August 1998 - August 2000
Tel Aviv University
Position
  • Senior Lecturer, Alon Fellow
Education
September 1987 - January 1991
University of Cambridge
Field of study
  • Photochemical Modeling of the Atmosphere
September 1984 - July 1987
King's College London
Field of study
  • First Class Double Honors BSc. In Physics & Chemistry

Publications

Publications (190)
Article
Full-text available
The human body is an incredible and complex sensing system. Environmental factors trigger a wide range of automatic neurophysiological responses. Biometric sensors can capture these responses in real time, providing clues about the underlying biophysical mechanisms. In this prototype study, we demonstrate an experimental paradigm to holistically ca...
Article
Full-text available
Electroencephalography (EEG) is a brain imaging technique in which electrodes are placed on the scalp. EEG signals are commonly decomposed into frequency bands called delta, theta, alpha, and beta. While these bands have been shown to be useful for characterizing various brain states, their utility as a one-size-fits-all analysis tool remains uncle...
Preprint
The human body is an incredible and complex sensing system. Environmental factors trigger a wide range of automatic neurophysiological responses. Biometric sensors can capture these responses in real time, providing clues to the underlying biophysical mechanisms. Here we show biometric variables can be used to accurately estimate ultra-local partic...
Preprint
Electroencephalography (EEG) is a brain imaging technique in which electrodes are placed on the scalp. EEG signals are commonly decomposed into frequency bands called delta, theta, alpha, and beta.While these bands have been shown to be useful for characterizing various brain states, their utility as a one-size-fits-all analysis tool remains unclea...
Article
Full-text available
Black pod rot, caused by Phytophthora palmivora , is a devastating disease of Theobroma cacao L. (cacao) leading to huge losses for farmers and limiting chocolate industry supplies. To understand resistance responses of cacao leaves to P. palmivora , Stage 2 leaves of genotypes Imperial College Selection 1 (ICS1), Colección Castro Naranjal 51 (CCN5...
Article
Full-text available
PM2.5, a type of fine particulate with a diameter equal to or less than 2.5 micrometers, has been identified as a major source of air pollution, and is associated with many health issues. Research on utilizing various data sources, such as remote sensing and in situ sensors, for PM2.5 concentrations modeling remains a hot topic. In this study, the...
Article
Full-text available
In this study, we present a nationwide machine learning model for hourly PM2.5 estimation for the continental United States (US) using high temporal resolution Geostationary Operational Environmental Satellites (GOES-16) Aerosol Optical Depth (AOD) data, meteorological variables from the European Center for Medium Range Weather Forecasting (ECMWF)...
Article
Full-text available
Sunlight incident on the Earth’s atmosphere is essential for life, and it is the driving force of a host of photo-chemical and environmental processes, such as the radiative heating of the atmosphere. We report the description and application of a physical methodology relative to how an ensemble of very low-cost sensors (with a total cost of <$20,...
Article
Full-text available
In this research, we present data‐driven forecasting of ionospheric total electron content (TEC) using the Long‐Short Term Memory (LSTM) deep recurrent neural network method. The random forest machine learning method was used to perform a regression analysis and estimate the variable importance of the input parameters. The input data are obtained f...
Chapter
By definition, human health and well-being are due to a complex interaction between a myriad of factors, a set of interactions for which we do not have a complete theoretical model, but often have an array of relevant data describing many aspects of this complex system. Machine learning is ideally suited for such situations. Over the last two decad...
Chapter
Airborne particulates are of particular significance for their human health impacts and their roles in both atmospheric radiative transfer and atmospheric chemistry. Observations of airborne particulates are typically made by environment agencies using rather expensive instruments. Due to the expense of the instruments usually used by environment a...
Article
Full-text available
This paper describes and demonstrates an autonomous robotic team that can rapidly learn the characteristics of environments that it has never seen before. The flexible paradigm is easily scalable to multi-robot, multi-sensor autonomous teams, and it is relevant to satellite calibration/validation and the creation of new remote sensing data products...
Preprint
Full-text available
This paper describes and demonstrates an autonomous robotic team that can rapidly learn the characteristics of environments that it has never seen before. The flexible paradigm is easily scalable to multi-robot, multi-sensor autonomous teams, and is relevant to satellite calibration/validation and the creation of new remote sensing data products. A...
Article
Full-text available
The “science-softCon UV/Vis⁺ Photochemistry Database” (www.photochemistry.org) is a large and comprehensive collection of EUV-VUV-UV-Vis-NIR spectral data and other photochemical information assembled from published peer-reviewed papers. The database contains photochemical data including absorption, fluorescence, photoelectron, and circular and lin...
Article
Full-text available
Airborne particulates are of particular significance for their human health impacts and their roles in both atmospheric radiative transfer and atmospheric chemistry. Observations of airborne particulates are typically made by environmental agencies using rather expensive instruments. Due to the expense of the instruments usually used by environment...
Preprint
The human body exhibits a variety of autonomic responses. For example, changing light intensity provokes a change in the pupil dilation. In the past, formulae for pupil size based on luminance have been derived using traditional empirical approaches. In this paper, we present a different approach to a similar task by using machine learning to ex- a...
Book
Spectral information (gas, liquid and solid phase from EUV-VUV-UV-Vis-NIR) and related data (e.g. information concerning publications on quantum yield studies or photolysis studies) from published papers. The 12th edition of the science-softCon "UV/Vis+ Spectra Data Base" CD-ROM series contains about 13500 spectra/data sheets (ascii-format) as well...
Article
CMOS IC technology has become an affordable means for implementing capable systems operating at 300 GHz and above. CMOS circuits have been used to generate a signal up to 1.3 THz to detect both amplitude and phase of signals up to 1.2 THz, and to detect a signal amplitude up to ~10 THz. Additionally, a transmitter and a receiver operating up to ~30...
Article
Full-text available
Approximately 50 million Americans have allergic diseases. Airborne plant pollen is a significant trigger for several of these allergic diseases. Ambrosia (ragweed) is known for its abundant production of pollen and its potent allergic effect in North America. Hence, estimating and predicting the daily atmospheric concentration of pollen (ragweed p...
Article
Full-text available
In this study, we found that machine learning was able to effectively estimate student learning outcomes geo-spatially across all the campuses in a large, urban, independent school district. The machine learning showed that key factors in estimating the student learning outcomes included the number of days students were absent from school. In turn,...
Article
Full-text available
In order to examine associations between asthma morbidity and local ambient air pollution in an area with relatively low levels of pollution, we conducted a time-series analysis of asthma hospital admissions and fine particulate matter pollution (PM2.5) in and around Jackson, MS, for the period 2003 to 2011. Daily patient-level records were obtaine...
Article
Full-text available
PM2.5 air pollution is a significant issue for human health all over the world, especially in East Asia. A large number of ground-based measurement sites have been established over the last decade to monitor real-time PM2.5 concentration. However, even this enhanced observational network leaves many gaps in characterizing the PM2.5 spatial distribu...
Article
Full-text available
For the period of the Barnett Coordinated Campaign, October 16–31, 2013, hourly concentrations for 46 volatile organic compounds (VOCs) were recorded at 14 air monitoring stations within the Barnett Shale of North Texas. These measurements are used to identify and analyze multi-species hydrocarbon signatures on a regional scale through the novel co...
Article
Full-text available
Millions of people have an allergic reaction to pollen. The impact of pollen allergies is on the rise due to increased pollen levels caused by global warming and the spread of highly invasive weeds. The production, release, and dispersal of pollen depend on the ambient weather conditions. The temperature, rainfall, humidity, cloud cover, and wind a...
Article
Full-text available
Allergies to airborne pollen are a significant issue affecting millions of Americans. Consequently, accurately predicting the daily concentration of airborne pollen is of significant public benefit in providing timely alerts. This study presents a method for the robust estimation of the concentration of airborne Ambrosia pollen using a suite of mac...
Article
Full-text available
A Global Ocean Carbon Algorithm Database (GOCAD) has been developed from over 500 oceanographic field campaigns conducted worldwide over the past 30 years including in situ reflectances and coincident satellite imagery, multi- and hyperspectral Chromophoric Dissolved Organic Matter (CDOM) absorption coefficients from 245–715 nm, CDOM spectral slope...
Article
Full-text available
In response to the challenge of military traumatic brain injury and posttraumatic stress disorder, the US military developed a wide range of holistic care modalities at the new Walter Reed National Military Medical Center, Bethesda, MD, from 2001 to 2017, guided by civilian expert consultation via the Epidaurus Project. These projects spanned a ran...
Chapter
Full-text available
Machine learning has found many applications in remote sensing. These applications range from retrieval algorithms to bias correction, from code acceleration to detection of disease in crops, from classification of pelagic habitats to rock type classification. As a broad subfield of artificial intelligence, machine learning is concerned with algori...
Article
Full-text available
This article describes an example of using machine learning to estimate the abundance of airborne Ambrosia pollen for Tulsa, OK. Twenty-seven years of historical pollen observations were used. These pollen observations were combined with machine learning and a very complete meteorological and land surface context of 85 variables to estimate the dai...
Article
Full-text available
The abundance of airborne particulate matter with an aerodynamic equivalent diameter of 2.5μm or less (PM2.5) is a significant environmental and health issue. Many tools have been used to examine the relationship between PM2.5 abundance and meteorological variables, but some of the relationships are nonlinear, non-Gaussian, and even unknown. Machin...
Article
Full-text available
Phytophthora megakarya (Pmeg) and Phytophthora palmivora (Ppal) cause black pod rot of Theobroma cacao L. (cacao). Of these two clade 4 species, Pmeg is more virulent and is displacing Ppal in many cacao production areas in Africa. Symptoms and species specific sporangia production were compared when the two species were co-inoculated onto pod piec...
Article
Full-text available
Phytophthora megakarya (Pmeg) and Phytophthora palmivora (Ppal) are closely related species causing cacao black pod rot. Although Ppal is a cosmopolitan pathogen, cacao is the only known host of economic importance for Pmeg. Pmeg is more virulent on cacao than Ppal. We sequenced and compared the Pmeg and Ppal genomes and identified virulence-relate...
Book
Spectral information (gas, liquid and solid phase from EUV-VUV-UV-Vis-NIR) and related data (e.g. information concerning publications on quantum yield studies or photolysis studies) from published papers. The 11th edition of the science-softCon "UV/Vis+ Spectra Data Base" contains about 10500 spectra/data sheets (ascii-format) as well as about 350...
Conference Paper
Recent advances of CMOS technology and circuits have made it an alternative for realizing capable and affordable THz systems. With process and circuit optimization, it should be possible to generate useful power and coherently detect signals at frequencies beyond 1THz, and incoherently detect signals at 40THz in CMOS.
Chapter
We describe the Ignite Distributed Collaborative Visualization System (IDCVS), a system which permits real-time interaction and visual collaboration around large data sets on thin devices for users distributed about the wide area. The IDCVS provides seamless interaction and immediate updates even under heavy load and when users are widely separated...
Article
There is an increasing awareness of the health impacts of particulate matter and a growing need to quantify the spatial and temporal variations of the global abundance of ground level airborne particulate matter (PM2.5). In March 2014, the World Health Organization (WHO) released a report that in 2012 alone, a staggering 7 million people died as a...
Article
Full-text available
Airborne particulates play a significant role in the atmospheric radiative balance and impact human health. To characterize this impact, global-scale observations and data products are needed. Satellite products allow for this global coverage but require in situ validations. This study used a remote-controlled aerial vehicle to look at the horizont...
Article
Full-text available
Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software ap...
Article
Hyperspectral cameras sample many different frequency bands at each pixel, enabling advanced detection algorithms. However, their limited spatial resolution and the need to measure the camera motion to create hyperspectral images makes them unsuitable for non-smooth moving platforms such as Unmanned Aerial Vehicles (UAVs). We present a procedure to...
Article
A model aircraft equipped with a custom laser-based, open-path methane sensor was deployed around a natural gas compressor station to quantify the methane leak rate and its variability at a compressor station in the Barnett Shale. The open-path, laser-based sensor provides fast (10 Hz) and precise (0.1 ppmv) measurements of methane in a compact pac...
Article
Full-text available
With the increasing awareness of health impacts of particulate matter, there is a growing need to comprehend the spatial and temporal variations of the global abundance of ground-level airborne particulate matter (PM₂.₅). Here we use a suite of remote sensing and meteorological data products together with ground based observations of PM₂.₅ from 8,3...
Article
Full-text available
Airborne particulates play a central role in both the earth's radiation balance and as a trigger for a wide range of health impacts. Air quality monitors are placed in networks across many cities globally. Typically these provide at best a few recording locations per city. However, large spatial variability occurs on the neighborhood scale. This st...
Book
Spectral information (gas, liquid and solid phase from EUV-VUV-UV-Vis-NIR) and related data (e.g. information concerning publications on quantum yield studies or photolysis studies) from published papers. This database is a work in permanent progress. Additional spectra and data sheets will be added continuously.
Article
Full-text available
With the increasing awareness of the health impacts of particulate matter, there is a growing need to comprehend the spatial and temporal variations of the global abundance of ground level airborne particulate matter with a diameter of 2.5 microns or less (PM2.5). Here we use a suite of remote sensing and meteorological data products together with...
Conference Paper
BigData should be a key component of a holistic approach to public health. There is increasing awareness that health is shaped by more than health care, but the exact causal pathway that links health to health behaviors, socioeconomic conditions, and environmental conditions has been inadequately explored by conventional epidemiologic metho...
Article
Full-text available
Human health is part of an interdependent multifaceted system. More than ever, we have increasingly large amounts of data on the body, both spatial and non-spatial, its systems, disease and our social and physical environment. These data have a geospatial component. An exciting new era is dawning where we are simultaneously collecting multiple data...
Article
Full-text available
With the increasing awareness of the health impacts of particulate matter there is a growing need to comprehend the spatial and temporal variations of the global abundance of ground level airborne particulate matter (PM2.5). Here we use a suite of remote sensing and meteorologi-cal data products together with ground based observations of PM2.5 from...